A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

Anomaly detection related books, papers, videos, and toolboxes

Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"

Supplementary material for SDM 19 paper "LSCP: Locally Selective Combination in Parallel Outlier Ensembles"

Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"

Detect EEG artifacts, outliers, or anomalies using supervised machine learning.

Implement of paper "Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures"